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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-finetuned-en-to-ar
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: un_multi
type: un_multi
args: ar-en
metrics:
- name: Bleu
type: bleu
value: 64.6767
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# opus-mt-en-ar-finetuned-en-to-ar
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the un_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8133
- Bleu: 64.6767
- Gen Len: 17.595
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log | 1.0 | 50 | 0.7710 | 64.3416 | 17.4 |
| No log | 2.0 | 100 | 0.7569 | 63.9546 | 17.465 |
| No log | 3.0 | 150 | 0.7570 | 64.7484 | 17.385 |
| No log | 4.0 | 200 | 0.7579 | 65.4073 | 17.305 |
| No log | 5.0 | 250 | 0.7624 | 64.8939 | 17.325 |
| No log | 6.0 | 300 | 0.7696 | 65.1257 | 17.45 |
| No log | 7.0 | 350 | 0.7747 | 65.527 | 17.395 |
| No log | 8.0 | 400 | 0.7791 | 65.1357 | 17.52 |
| No log | 9.0 | 450 | 0.7900 | 65.3812 | 17.415 |
| 0.3982 | 10.0 | 500 | 0.7925 | 65.7346 | 17.39 |
| 0.3982 | 11.0 | 550 | 0.7951 | 65.1267 | 17.62 |
| 0.3982 | 12.0 | 600 | 0.8040 | 64.6874 | 17.495 |
| 0.3982 | 13.0 | 650 | 0.8069 | 64.7788 | 17.52 |
| 0.3982 | 14.0 | 700 | 0.8105 | 64.6701 | 17.585 |
| 0.3982 | 15.0 | 750 | 0.8120 | 64.7111 | 17.58 |
| 0.3982 | 16.0 | 800 | 0.8133 | 64.6767 | 17.595 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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